ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE

Jinming Zhang

doi:10.1002/j.2333-8504.2005.tb01981.x

ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE

Research output: Contribution to journal › Article › peer-review

Abstract

This study derived an expectation‐maximization (EM) algorithm for estimating the parameters of multidimensional item response models. A genetic algorithm (GA) was developed to be used in the maximization step in each EM cycle. The focus of the EM‐GA algorithm developed in this paper was on multidimensional items with mixed structure. Simulated item response data were generated and then estimated by a computer program based on the EM‐GA algorithm. The simulation results demonstrate that the EM‐GA algorithm is a very promising approach in estimating multidimensional item response model parameters.

Original language	English (US)
Pages (from-to)	i-38
Journal	ETS Research Report Series
Volume	2005
Issue number	1
DOIs	https://doi.org/10.1002/j.2333-8504.2005.tb01981.x
State	Published - Jun 1 2005
Externally published	Yes

Keywords

genetic algorithm
GA
EM-GA algorithm
ASSEST
estimation
multidimensional item response theory
MIRT
mixed structure
approximate simple structure

Access to Document

10.1002/j.2333-8504.2005.tb01981.x

Cite this

@article{e44f28ca521d4326b9866114cb61c88a,

title = "ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE",

abstract = "This study derived an expectation‐maximization (EM) algorithm for estimating the parameters of multidimensional item response models. A genetic algorithm (GA) was developed to be used in the maximization step in each EM cycle. The focus of the EM‐GA algorithm developed in this paper was on multidimensional items with mixed structure. Simulated item response data were generated and then estimated by a computer program based on the EM‐GA algorithm. The simulation results demonstrate that the EM‐GA algorithm is a very promising approach in estimating multidimensional item response model parameters.",

keywords = "genetic algorithm, GA, EM-GA algorithm, ASSEST, estimation, multidimensional item response theory, MIRT, mixed structure, approximate simple structure",

author = "Jinming Zhang",

year = "2005",

month = jun,

day = "1",

doi = "10.1002/j.2333-8504.2005.tb01981.x",

language = "English (US)",

volume = "2005",

pages = "i--38",

journal = "ETS Research Report Series",

issn = "2330-8516",

publisher = "John Wiley & Sons, Ltd.",

number = "1",

}

TY - JOUR

T1 - ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE

AU - Zhang, Jinming

PY - 2005/6/1

Y1 - 2005/6/1

N2 - This study derived an expectation‐maximization (EM) algorithm for estimating the parameters of multidimensional item response models. A genetic algorithm (GA) was developed to be used in the maximization step in each EM cycle. The focus of the EM‐GA algorithm developed in this paper was on multidimensional items with mixed structure. Simulated item response data were generated and then estimated by a computer program based on the EM‐GA algorithm. The simulation results demonstrate that the EM‐GA algorithm is a very promising approach in estimating multidimensional item response model parameters.

AB - This study derived an expectation‐maximization (EM) algorithm for estimating the parameters of multidimensional item response models. A genetic algorithm (GA) was developed to be used in the maximization step in each EM cycle. The focus of the EM‐GA algorithm developed in this paper was on multidimensional items with mixed structure. Simulated item response data were generated and then estimated by a computer program based on the EM‐GA algorithm. The simulation results demonstrate that the EM‐GA algorithm is a very promising approach in estimating multidimensional item response model parameters.

KW - genetic algorithm

KW - GA

KW - EM-GA algorithm

KW - ASSEST

KW - estimation

KW - multidimensional item response theory

KW - MIRT

KW - mixed structure

KW - approximate simple structure

U2 - 10.1002/j.2333-8504.2005.tb01981.x

DO - 10.1002/j.2333-8504.2005.tb01981.x

M3 - Article

VL - 2005

SP - i-38

JO - ETS Research Report Series

JF - ETS Research Report Series

SN - 2330-8516

IS - 1

ER -

ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE

Abstract

Keywords

Access to Document

Fingerprint

Cite this